An ancestral recombination graph of human, Neanderthal, and Denisovan genomes

Enrichment of a subset of Neanderthal polymorphisms in autistic probands and siblings

Homo sapiens and Neanderthals underwent hybridization during the Middle/Upper Paleolithic age, culminating in retention of small amounts of Neanderthal-derived DNA in the modern human genome. In the current study, we address the potential roles Neanderthal single nucleotide polymorphisms (SNP) may be playing in autism susceptibility in samples of black non-Hispanic, white Hispanic, and white non-Hispanic people using data from the Simons Foundation Powering Autism Research (SPARK), Genotype-Tissue Expression (GTEx), and 1000 Genomes (1000G) databases. We have discovered that rare variants are significantly enriched in autistic probands compared to race-matched controls. In addition, we have identified 25 rare and common SNPs that are significantly enriched in autism on different ethnic backgrounds, some of which show significant clinical associations. We have also identified other SNPs that share more specific genotype-phenotype correlations but which are not necessarily enriched in autism and yet may nevertheless play roles in comorbid phenotype expression (e.g., intellectual disability, epilepsy, and language regression). These results strongly suggest Neanderthal-derived DNA is playing a significant role in autism susceptibility across major populations in the United States.

A general and efficient representation of ancestral recombination graphs

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. This approach is out of step with modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalises these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

The genetic changes that shaped Neandertals, Denisovans, and modern humans

Modern human ancestors diverged from the ancestors of Neandertals and Denisovans about 600,000 years ago. Until about 40,000 years ago, these three groups existed in parallel, occasionally met, and exchanged genes. A critical question is why modern humans, and not the other two groups, survived, became numerous, and developed complex cultures. Here, we discuss genetic differences among the groups and some of their functional consequences. As more present-day genome sequences become available from diverse groups, we predict that very few, if any, differences will distinguish all modern humans from all Neandertals and Denisovans. We propose that the genetic basis of what constitutes a modern human is best thought of as a combination of genetic features, where perhaps none of them is present in each and every present-day individual.

Ancient genomes and the evolutionary path of modern humans

Growing evidence from archaic and early modern human genomes brings new insights to the emergence of modern humans. We recount recent information collected from ancient DNA studies that inform us about the evolutionary pathway to modern humanity. These findings point to both individual- and population-level advantages underlying modern human expansion.

The Promise of Inferring the Past Using the Ancestral Recombination Graph

The ancestral recombination graph (ARG) is a structure that represents the history of coalescent and recombination events connecting a set of sequences (Hudson RR. In: Futuyma D, Antonovics J, editors. Gene genealogies and the coalescent process. In: Oxford Surveys in Evolutionary Biology; 1991. p. 1 to 44.). The full ARG can be represented as a set of genealogical trees at every locus in the genome, annotated with recombination events that change the topology of the trees between adjacent loci and the mutations that occurred along the branches of those trees (Griffiths RC, Marjoram P. An ancestral recombination graph. In: Donnelly P, Tavare S, editors. Progress in population genetics and human evolution. Springer; 1997. p. 257 to 270.). Valuable insights can be gained into past evolutionary processes, such as demographic events or the influence of natural selection, by studying the ARG. It is regarded as the "holy grail" of population genetics (Hubisz M, Siepel A. Inference of ancestral recombination graphs using ARGweaver. In: Dutheil JY, editors. Statistical population genomics. New York, NY: Springer US; 2020. p. 231-266.) since it encodes the processes that generate all patterns of allelic and haplotypic variation from which all commonly used summary statistics in population genetic research (e.g. heterozygosity and linkage disequilibrium) can be derived. Many previous evolutionary inferences relied on summary statistics extracted from the genotype matrix. Evolutionary inferences using the ARG represent a significant advancement as the ARG is a representation of the evolutionary history of a sample that shows the past history of recombination, coalescence, and mutation events across a particular sequence. This representation in theory contains as much information, if not more, than the combination of all independent summary statistics that could be derived from the genotype matrix. Consistent with this idea, some of the first ARG-based analyses have proven to be more powerful than summary statistic-based analyses (Speidel L, Forest M, Shi S, Myers SR. A method for genome-wide genealogy estimation for thousands of samples. Nat Genet. 2019:51(9):1321 to 1329.; Stern AJ, Wilton PR, Nielsen R. An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data. PLoS Genet. 2019:15(9):e1008384.; Hubisz MJ, Williams AL, Siepel A. Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph. PLoS Genet. 2020:16(8):e1008895.; Fan C, Mancuso N, Chiang CWK. A genealogical estimate of genetic relationships. Am J Hum Genet. 2022:109(5):812-824.; Fan C, Cahoon JL, Dinh BL, Ortega-Del Vecchyo D, Huber C, Edge MD, Mancuso N, Chiang CWK. A likelihood-based framework for demographic inference from genealogical trees. bioRxiv. 2023.10.10.561787. 2023.; Hejase HA, Mo Z, Campagna L, Siepel A. A deep-learning approach for inference of selective sweeps from the ancestral recombination graph. Mol Biol Evol. 2022:39(1):msab332.; Link V, Schraiber JG, Fan C, Dinh B, Mancuso N, Chiang CWK, Edge MD. Tree-based QTL mapping with expected local genetic relatedness matrices. bioRxiv. 2023.04.07.536093. 2023.; Zhang BC, Biddanda A, Gunnarsson ÁF, Cooper F, Palamara PF. Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nat Genet. 2023:55(5):768-776.). As such, there has been significant interest in the field to investigate 2 main problems related to the ARG: (i) How can we estimate the ARG based on genomic data, and (ii) how can we extract information of past evolutionary processes from the ARG? In this perspective, we highlight 3 topics that pertain to these main issues: The development of computational innovations that enable the estimation of the ARG; remaining challenges in estimating the ARG; and methodological advances for deducing evolutionary forces and mechanisms using the ARG. This perspective serves to introduce the readers to the types of questions that can be explored using the ARG and to highlight some of the most pressing issues that must be addressed in order to make ARG-based inference an indispensable tool for evolutionary research.

More than a decade of genetic research on the Denisovans

Denisovans, a group of now extinct humans who lived in Eastern Eurasia in the Middle and Late Pleistocene, were first identified from DNA sequences just over a decade ago. Only ten fragmentary remains from two sites have been attributed to Denisovans based entirely on molecular information. Nevertheless, there has been great interest in using genetic data to understand Denisovans and their place in human history. From the reconstruction of a single high-quality genome, it has been possible to infer their population history, including events of admixture with other human groups. Additionally, the identification of Denisovan DNA in the genomes of present-day individuals has provided insights into the timing and routes of dispersal of ancient modern humans into Asia and Oceania, as well as the contributions of archaic DNA to the physiology of present-day people. In this Review, we synthesize more than a decade of research on Denisovans, reconcile controversies and summarize insights into their population history and phenotype. We also highlight how our growing knowledge about Denisovans has provided insights into our own evolutionary history.

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

Pharmacogenetic Variation in Neanderthals and Denisovans and Implications for Human Health and Response to Medications

Modern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes-genes responsible for the processing of exogenous substances such as food, pollutants, and medications-as these can relate to changing environmental effects, and beneficial variants may have been retained as modern humans encountered new environments. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remain understudied. Here, we explore 11 key cytochrome P450 genes (CYP450) involved in 75% of all drug metabolizing reactions in three Neanderthal and one Denisovan individuals and examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these 11 CYP450 genes in archaic individuals and find important predicted phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaic CYP450 genes, which may result in altered metabolism in living people carrying these variants. We also identified several variants in the archaic CYP450 genes that are novel and unique to archaic humans as well as one gene, CYP2B6, that shows evidence for a gene duplication found only in Neanderthals and modern Africans. Finally, we highlight CYP2A6, CYP2C9, and CYP2J2, genes which show evidence for archaic introgression into modern humans and posit evolutionary hypotheses that explain their allele frequencies in modern populations.

Archaic Introgression Shaped Human Circadian Traits

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

The era of the ARG: an empiricist's guide to ancestral recombination graphs

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in empirical evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

Human-specific genetics: new tools to explore the molecular and cellular basis of human evolution

Our ancestors acquired morphological, cognitive and metabolic modifications that enabled humans to colonize diverse habitats, develop extraordinary technologies and reshape the biosphere. Understanding the genetic, developmental and molecular bases for these changes will provide insights into how we became human. Connecting human-specific genetic changes to species differences has been challenging owing to an abundance of low-effect size genetic changes, limited descriptions of phenotypic differences across development at the level of cell types and lack of experimental models. Emerging approaches for single-cell sequencing, genetic manipulation and stem cell culture now support descriptive and functional studies in defined cell types with a human or ape genetic background. In this Review, we describe how the sequencing of genomes from modern and archaic hominins, great apes and other primates is revealing human-specific genetic changes and how new molecular and cellular approaches - including cell atlases and organoids - are enabling exploration of the candidate causal factors that underlie human-specific traits.

Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We published LDGMs and ancestry-specific LDGM precision matrices for 18 million common variants (minor allele frequency >1%) in five ancestry groups, validated their accuracy and demonstrated order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implemented an extremely fast multiancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally diverse genetic association data across millions of variants and individuals.

Mitochondrial DNA in Human Diversity and Health: From the Golden Age to the Omics Era

Mitochondrial DNA (mtDNA) is a small fraction of our hereditary material. However, this molecule has had an overwhelming presence in scientific research for decades until the arrival of high-throughput studies. Several appealing properties justify the application of mtDNA to understand how human populations are-from a genetic perspective-and how individuals exhibit phenotypes of biomedical importance. Here, I review the basics of mitochondrial studies with a focus on the dawn of the field, analysis methods and the connection between two sides of mitochondrial genetics: anthropological and biomedical. The particularities of mtDNA, with respect to inheritance pattern, evolutionary rate and dependence on the nuclear genome, explain the challenges of associating mtDNA composition and diseases. Finally, I consider the relevance of this single locus in the context of omics research. The present work may serve as a tribute to a tool that has provided important insights into the past and present of humankind.

Polysaccharide-Based Stimulus-Responsive Nanomedicines for Combination Cancer Immunotherapy

Cancer immunotherapy is a promising antitumor approach, whereas nontherapeutic side effects, tumor microenvironment (TME) intricacy, and low tumor immunogenicity limit its therapeutic efficacy. In recent years, combination immunotherapy with other therapies has been proven to considerably increase antitumor efficacy. However, achieving codelivery of the drugs to the tumor site remains a major challenge. Stimulus-responsive nanodelivery systems show controlled drug delivery and precise drug release. Polysaccharides, a family of potential biomaterials, are widely used in the development of stimulus-responsive nanomedicines due to their unique physicochemical properties, biocompatibility, and modifiability. Here, the antitumor activity of polysaccharides and several combined immunotherapy strategies (e.g., immunotherapy combined with chemotherapy, photodynamic therapy, or photothermal therapy) are summarized. More importantly, the recent progress of polysaccharide-based stimulus-responsive nanomedicines for combination cancer immunotherapy is discussed, with the focus on construction of nanomedicine, targeted delivery, drug release, and enhanced antitumor effects. Finally, the limitations and application prospects of this new field are discussed.

Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits

Genome-wide genealogies compactly represent the evolutionary history of a set of genomes and inferring them from genetic data has the potential to facilitate a wide range of analyses. We introduce a method, ARG-Needle, for accurately inferring biobank-scale genealogies from sequencing or genotyping array data, as well as strategies to utilize genealogies to perform association and other complex trait analyses. We use these methods to build genome-wide genealogies using genotyping data for 337,464 UK Biobank individuals and test for association across seven complex traits. Genealogy-based association detects more rare and ultra-rare signals (N = 134, frequency range 0.0007-0.1%) than genotype imputation using ~65,000 sequenced haplotypes (N = 64). In a subset of 138,039 exome sequencing samples, these associations strongly tag (average r = 0.72) underlying sequencing variants enriched (4.8×) for loss-of-function variation. These results demonstrate that inferred genome-wide genealogies may be leveraged in the analysis of complex traits, complementing approaches that require the availability of large, population-specific sequencing panels.

Archaic humans have contributed to large-scale variation in modern human T cell receptor genes

Human T cell receptors (TCRs) are critical for mediating immune responses to pathogens and tumors and regulating self-antigen recognition. Yet, variations in the genes encoding TCRs remain insufficiently defined. Detailed analysis of expressed TCR alpha, beta, gamma, and delta genes in 45 donors from four human populations-African, East Asian, South Asian, and European-revealed 175 additional TCR variable and junctional alleles. Most of these contained coding changes and were present at widely differing frequencies in the populations, a finding confirmed using DNA samples from the 1000 Genomes Project. Importantly, we identified three Neanderthal-derived, introgressed TCR regions including a highly divergent TRGV4 variant, which mediated altered butyrophilin-like molecule 3 (BTNL3) ligand reactivity and was frequent in all modern Eurasian population groups. Our results demonstrate remarkable variation in TCR genes in both individuals and populations, providing a strong incentive for including allelic variation in studies of TCR function in human biology.

Homo sapiens—A Species Not Designed for Space Flight: Health Risks in Low Earth Orbit and Beyond, Including Potential Risks When Traveling beyond the Geomagnetic Field of Earth

Homo sapiens and their predecessors evolved in the context of the boundary conditions of Earth, including a 1 g gravity and a geomagnetic field (GMF). These variables, plus others, led to complex organisms that evolved under a defined set of conditions and define how humans will respond to space flight, a circumstance that could not have been anticipated by evolution. Over the past ~60 years, space flight and living in low Earth orbit (LEO) have revealed that astronauts are impacted to varying degrees by such new environments. In addition, it has been noted that astronauts are quite heterogeneous in their response patterns, indicating that such variation is either silent if one remained on Earth, or the heterogeneity unknowingly contributes to disease development during aging or in response to insults. With the planned mission to deep space, humans will now be exposed to further risks from radiation when traveling beyond the influence of the GMF, as well as other potential risks that are associated with the actual loss of the GMF on the astronauts, their microbiomes, and growing food sources. Experimental studies with model systems have revealed that hypogravity conditions can influence a variety biological and physiological systems, and thus the loss of the GMF may have unanticipated consequences to astronauts’ systems, such as those that are electrical in nature (i.e., the cardiovascular system and central neural systems). As astronauts have been shown to be heterogeneous in their responses to LEO, they may require personalized countermeasures, while others may not be good candidates for deep-space missions if effective countermeasures cannot be developed for long-duration missions. This review will discuss several of the physiological and neural systems that are affected and how the emerging variables may influence astronaut health and functioning.

Homo sapiens and Neanderthals share high cerebral cortex integration into adulthood

There is controversy around the mechanisms that guided the change in brain shape during the evolution of modern humans. It has long been held that different cortical areas evolved independently from each other to develop their unique functional specializations. However, some recent studies suggest that high integration between different cortical areas could facilitate the emergence of equally extreme, highly specialized brain functions. Here, we analyse the evolution of brain shape in primates using three-dimensional geometric morphometrics of endocasts. We aim to determine, firstly, whether modern humans present unique developmental patterns of covariation between brain cortical areas; and secondly, whether hominins experienced unusually high rates of evolution in brain covariation as compared to other primates. On the basis of analyses including modern humans and other extant great apes at different developmental stages, we first demonstrate that, unlike our closest living relatives, Homo sapiens retain high levels of covariation between cortical areas into adulthood. Among the other great apes, high levels of covariation are only found in immature individuals. Secondly, at the macro-evolutionary level, our analysis of 400 endocasts, representing 148 extant primate species and 6 fossil hominins, shows that strong covariation between different areas of the brain in H. sapiens and Homo neanderthalensis evolved under distinctly higher evolutionary rates than in any other primate, suggesting that natural selection favoured a greatly integrated brain in both species. These results hold when extinct species are excluded and allometric effects are accounted for. Our findings demonstrate that high covariation in the brain may have played a critical role in the evolution of unique cognitive capacities and complex behaviours in both modern humans and Neanderthals.

Dual-Cascade Responsive Nanoparticles Enhance Pancreatic Cancer Therapy by Eliminating Tumor-Resident Intracellular Bacteria

The limited drug penetration and robust bacteria-mediated drug inactivation in pancreatic cancer result in the failure of chemotherapy. To fight against these issues, a dual-cascade responsive nanoparticle (sNP@G/IR) that can sequentially trigger deep penetration, killing of intratumor bacteria, and controlled release of chemo-drug, is reported. sNP@G/IR consists of a hyaluronic acid (HA) shell and glutathione (GSH)-responsive polymer-core (NP@G/IR), that encapsulates gemcitabine (Gem) and photothermal agent (IR1048). The polymer core, as an antibiotic alternative, is tailored to exert optimal antibacterial activity and selectivity. sNP@G/IR actively homes in on the tumor due to the CD44 targeting of the HA shell, which is subsequently degraded by the hyaluronidase in the extracellular matrix. The resultant NP@G/IR in decreased size and reversed charge facilitates deep tumor penetration. After cellular endocytosis, the exposed guanidine on NP@G/IR kills intracellular bacteria through disrupting cell membranes. Intracellular GSH further triggers the controlled release of the cargo. Thus, the protected Gem eventually induces cell apoptosis. Under laser irradiation, the hyperthermia of IR1048 helps further elimination of tumors and bacteria. Moreover, sNP@G/IR activates immune response, thereby reinforcing anticancer capacity. Therefore, this dual-cascade responsive sNP@G/IR eliminates tumor-resident intracellular bacteria and augments drug delivery efficacy, providing a new avenue for improving cancer therapy.

Neandertal introgression partitions the genetic landscape of neuropsychiatric disorders and associated behavioral phenotypes

Despite advances in identifying the genetic basis of psychiatric and neurological disorders, fundamental questions about their evolutionary origins remain elusive. Here, introgressed variants from archaic humans such as Neandertals can serve as an intriguing research paradigm. We compared the number of associations for Neandertal variants to the number of associations of frequency-matched non-archaic variants with regard to human CNS disorders (neurological and psychiatric), nervous system drug prescriptions (as a proxy for disease), and related, non-disease phenotypes in the UK biobank (UKBB). While no enrichment for Neandertal genetic variants were observed in the UKBB for psychiatric or neurological disease categories, we found significant associations with certain behavioral phenotypes including pain, chronotype/sleep, smoking and alcohol consumption. In some instances, the enrichment signal was driven by Neandertal variants that represented the strongest association genome-wide. SNPs within a Neandertal haplotype that was associated with smoking in the UKBB could be replicated in four independent genomics datasets.Our data suggest that evolutionary processes in recent human evolution like admixture with Neandertals significantly contribute to behavioral phenotypes but not psychiatric and neurological diseases. These findings help to link genetic variants in a population to putative past beneficial effects, which likely only indirectly contribute to pathology in modern day humans.

The contribution of Neanderthal introgression to modern human traits

Neanderthals, our closest extinct relatives, lived in western Eurasia from 400,000 years ago until they went extinct around 40,000 years ago. DNA retrieved from ancient specimens revealed that Neanderthals mated with modern human contemporaries. As a consequence, introgressed Neanderthal DNA survives scattered across the human genome such that 1-4% of the genome of present-day people outside Africa are inherited from Neanderthal ancestors. Patterns of Neanderthal introgressed genomic sequences suggest that Neanderthal alleles had distinct fates in the modern human genetic background. Some Neanderthal alleles facilitated human adaptation to new environments such as novel climate conditions, UV exposure levels and pathogens, while others had deleterious consequences. Here, we review the body of work on Neanderthal introgression over the past decade. We describe how evolutionary forces shaped the genomic landscape of Neanderthal introgression and highlight the impact of introgressed alleles on human biology and phenotypic variation.

Molecular diversity and phenotypic pleiotropy of ancient genomic regulatory loci derived from human endogenous retrovirus type H (HERVH) promoter LTR7 and HERVK promoter LTR5_Hs and their contemporary impacts on pathophysiology of Modern Humans

Timelines of population-level effects of viruses on humans varied from the evolutionary scale of million years to contemporary spread of viral infections. Correspondingly, these events are exemplified by: (i) emergence of human endogenous retroviruses (HERVs) from ancient germline infections leading to stable integration of viral genomes into human chromosomes; and (ii) wide-spread viral infections reaching a global pandemic state such as the COVID-19 pandemic. Despite significant efforts, understanding of HERV’s roles in governance of genomic regulatory networks, their impacts on primate evolution and development of human-specific physiological and pathological phenotypic traits remains limited. Remarkably, present analyses revealed that expression of a dominant majority of genes (1696 of 1944 genes; 87%) constituting high-confidence down-steam regulatory targets of defined HERV loci was significantly altered in cells infected with the SARS-CoV-2 coronavirus, a pathogen causing the global COVID-19 pandemic. This study focused on defined sub-sets of DNA sequences derived from HERVs that are expressed at specific stages of human preimplantation embryogenesis and exert regulatory actions essential for self-renewal and pluripotency. Evolutionary histories of LTR7/HERVH and LTR5_Hs/HERVK were charted based on evidence of the earliest presence and expansion of highly conserved (HC) LTR sequences. Sequence conservation analyses of most recent releases 17 primate species’ genomes revealed that LTR7/HERVH have entered germlines of primates in Africa after the separation of the New World Monkey lineage, while LTR5_Hs/HERVK successfully colonized primates’ germlines after the segregation of Gibbons’ species. Subsequently, both LTR7 and LTR5_Hs undergo a marked ~ fourfold–fivefold expansion in genomes of Great Apes. Timelines of quantitative expansion of both LTR7 and LTR5_Hs loci during evolution of Great Apes appear to replicate the consensus evolutionary sequence of increasing cognitive and behavioral complexities of non-human primates, which seems particularly striking for LTR7 loci and 11 distinct LTR7 subfamilies. Consistent with previous reports, identified in this study, 351 human-specific (HS) insertions of LTR7 (175 loci) and LTR5_Hs (176 loci) regulatory sequences have been linked to genes implicated in establishment and maintenance of naïve and primed pluripotent states and preimplantation embryogenesis phenotypes. Unexpectedly, HS-LTRs manifest regulatory connectivity to genes encoding markers of 12 distinct cells’ populations of fetal gonads, as well as genes implicated in physiology and pathology of human spermatogenesis, including Y-linked spermatogenic failure, oligo- and azoospermia. Granular interrogations of genes linked with 11 distinct LTR7 subfamilies revealed that mammalian offspring survival (MOS) genes seem to remain one of consistent regulatory targets throughout ~ 30 MYA of the divergent evolution of LTR7 loci. Differential GSEA of MOS versus non-MOS genes identified clearly discernable dominant enrichment patterns of phenotypic traits affected by MOS genes linked with LTR7 (562 MOS genes) and LTR5_Hs (126 MOS genes) regulatory loci across the large panel of genomics and proteomics databases reflecting a broad spectrum of human physiological and pathological traits. GSEA of LTR7-linked MOS genes identified more than 2200 significantly enriched records of human common and rare diseases and gene signatures of 466 significantly enriched records of Human Phenotype Ontology traits, including Autosomal Dominant (92 genes) and Autosomal Recessive (93 genes) Inheritance. LTR7 regulatory elements appear linked with genes implicated in functional and morphological features of central nervous system, including synaptic transmission and protein–protein interactions at synapses, as well as gene signatures differentially regulated in cells of distinct neurodevelopmental stages and morphologically diverse cell types residing and functioning in human brain. These include Neural Stem/Precursor cells, Radial Glia cells, Bergman Glia cells, Pyramidal cells, Tanycytes, Immature neurons, Interneurons, Trigeminal neurons, GABAergic neurons, and Glutamatergic neurons. GSEA of LTR7-linked genes identified significantly enriched gene sets encoding markers of more than 80 specialized types of neurons and markers of 521 human brain regions, most prominently, subiculum and dentate gyrus. Identification and characterization of 1944 genes comprising high-confidence down-steam regulatory targets of LTR7 and/or LTR5_Hs loci validated and extended these observations by documenting marked enrichments for genes implicated in neoplasm metastasis, intellectual disability, autism, multiple cancer types, Alzheimer’s, schizophrenia, and other brain disorders. Overall, genes representing down-stream regulatory targets of ancient retroviral LTRs exert the apparently cooperative and exceedingly broad phenotypic impacts on human physiology and pathology. This is exemplified by altered expression of 93% high-confidence LTR targets in cells infected by contemporary viruses, revealing a convergence of virus-inflicted aberrations on genomic regulatory circuitry governed by ancient retroviral LTR elements and interference with human cells’ differentiation programs.

Temporal mapping of derived high-frequency gene variants supports the mosaic nature of the evolution of Homo sapiens

Large-scale estimations of the time of emergence of variants are essential to examine hypotheses concerning human evolution with precision. Using an open repository of genetic variant age estimations, we offer here a temporal evaluation of various evolutionarily relevant datasets, such as Homo sapiens-specific variants, high-frequency variants found in genetic windows under positive selection, introgressed variants from extinct human species, as well as putative regulatory variants specific to various brain regions. We find a recurrent bimodal distribution of high-frequency variants, but also evidence for specific enrichments of gene categories in distinct time windows, pointing to different periods of phenotypic changes, resulting in a mosaic. With a temporal classification of genetic mutations in hand, we then applied a machine learning tool to predict what genes have changed more in certain time windows, and which tissues these genes may have impacted more. Overall, we provide a fine-grained temporal mapping of derived variants in Homo sapiens that helps to illuminate the intricate evolutionary history of our species.

Carrier Free O2 -Economizer for Photodynamic Therapy Against Hypoxic Tumor by Inhibiting Cell Respiration

Abnormal tumor metabolism causes the hypoxic microenvironment, which greatly limits the efficacy of photodynamic therapy (PDT). In this work, a strategy of metabolic reprogramming is proposed to economize O₂ for enhanced PDT against hypoxic tumors. The carrier-free O₂ -economizer (designated as LonCe) is prepared based on the metabolic antitumor drug of Lonidamine (Lon) and the photosensitizer of chlorin e6 (Ce6). By virtue of intermolecular interactions, Lon and Ce6 self-assemble into nanosized LonCe with favorable stability and high drug contents. Compared with Ce6, LonCe exhibits an improved cellular uptake and photodynamic property for tumor treatment. Moreover, LonCe is capable of inhibiting cell metabolism and mitochondrial respiration to remit the tumor hypoxia, which would promote reactive oxygen species (ROS) production and elevate the PDT efficacy on tumor suppression. In vivo experiments indicate that intravenously injected LonCe prefers to accumulate at the tumor site for highly efficient PDT regardless of the hypoxic environment. Besides, the self-delivery LonCe is fabricated without any carriers, which avoids the excipients induced system toxicity and immunogenicity in vivo. This carrier-free nanomedicine with cell respiratory inhibition mechanism would expedite the development and clinical translation of photodynamic nanoplatforms in tumor treatment.

Bioinspired Lipoproteins of Furoxans-Oxaliplatin Remodel Physical Barriers in Tumor to Potentiate T-Cell Infiltration

The infiltration of cytotoxic T lymphocytes (CTLs) in tumors is critically challenged by the intricate intratumor physical barriers, which is emerging as an important issue of anticancer immunotherapy. Herein, a reduction-sensitive nitric oxide donor conjugate of furoxans-oxaliplatin is synthesized and a stroma-cell-accessible bioinspired lipoprotein system (S-LFO) is designed, aiming to facilitate CTL infiltration in tumors for anticancer immunotherapy. S-LFO treatment significantly promotes tumor vessel normalization and eliminates multiple components of tumor stroma, ultimately producing a 2.96-fold, 5.02-fold, and 8.65-fold increase of CD3⁺ CD8⁺ T cells, their interferon-γ- and granzyme B-expressing subtypes when comparing to the negative control, and considerably facilitating their trafficking to the cancer cell regions in tumors. Moreover, the combination of S-LFO with an antiprogrammed death ligand-1 produces notable therapeutic benefits of retarded tumor growth and extends survivals in three murine tumor models. Therefore, this study provides an encouraging strategy of remodeling the intratumor physical barriers to potentiate CTL infiltration for anticancer immunotherapy.

Fibroblast Activation Protein-α Responsive Peptide Assembling Prodrug Nanoparticles for Remodeling the Immunosuppressive Microenvironment and Boosting Cancer Immunotherapy

Checkpoint blockade immunotherapy has broad application prospects in the clinical treatment of malignant tumors. However, the low response rate of the checkpoint blockade is due to low tumor immunogenicity and immunosuppression within the tumor microenvironment. Herein, the authors design an amphiphilic bifunctional PD-1/PD-L1 peptide antagonist PCP, and co-deliver doxorubicin (DOX) and R848 through co-assembly of a multi-agent prodrug (PCP@R848/DOX), which can be specifically cleaved by fibroblast activation protein-α (FAP-α) in the tumor stroma. Upon reaching the tumor tissue, the PCP@R848/DOX prodrug nanostructure is disassembled by FAP-α. The localized release of DOX and R848 triggers immunogenic cell death (ICD) and reprograms tumor-associated macrophages (TAMs) to elicit antitumor immunity. Furthermore, sustained release of PD-1 or PD-L1 peptide antagonists mediates the PD-L1 pathway blockade for further propagated activation of cytotoxic T lymphocytes. Notably, a tumor microenvironment activatable prodrug nanoparticle is presented for triple-modality cancer therapy that functions by simultaneously activating ICD and altering the phenotype of TAMs when combined with PD-1 blockade therapy, which efficiently elicits a strong systemic antitumor immune response. This strategy may emerge as a new paradigm in the treatment of cancer by combination immunotherapy.

Inferring human evolutionary history

Unified genetic genealogy improves our understanding of how humans evolved.

A unified genealogy of modern and ancient genomes

The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.

Candidate‐species delimitation in Desmognathus salamanders reveals gene flow across lineage boundaries, confounding phylogenetic estimation and clarifying hybrid zones

Dusky Salamanders (genus Desmognathus) currently comprise only 22 described, extant species. However, recent mitochondrial and nuclear estimates indicate the presence of up to 49 candidate species based on ecogeographic sampling. Previous studies also suggest a complex history of hybridization between these lineages. Studies in other groups suggest that disregarding admixture may affect both phylogenetic inference and clustering‐based species delimitation. With a dataset comprising 233 Anchored Hybrid Enrichment (AHE) loci sequenced for 896 Desmognathus specimens from all 49 candidate species, we test three hypotheses regarding (i) species‐level diversity, (ii) hybridization and admixture, and (iii) misleading phylogenetic inference. Using phylogenetic and population‐clustering analyses considering gene flow, we find support for at least 47 candidate species in the phylogenomic dataset, some of which are newly characterized here while others represent combinations of previously named lineages that are collapsed in the current dataset. Within these, we observe significant phylogeographic structure, with up to 64 total geographic genetic lineages, many of which hybridize either narrowly at contact zones or extensively across ecological gradients. We find strong support for both recent admixture between terminal lineages and ancient hybridization across internal branches. This signal appears to distort concatenated phylogenetic inference, wherein more heavily admixed terminal specimens occupy apparently artifactual early‐diverging topological positions, occasionally to the extent of forming false clades of intermediate hybrids. Additional geographic and genetic sampling and more robust computational approaches will be needed to clarify taxonomy, and to reconstruct a network topology to display evolutionary relationships in a manner that is consistent with their complex history of reticulation.

Tumor-Microenvironment-Responsive Nanomedicine for Enhanced Cancer Immunotherapy

The past decades have witnessed great progress in cancer immunotherapy, which has profoundly revolutionized oncology, whereas low patient response rates and potential immune-related adverse events remain major clinical challenges. With the advantages of controlled delivery and modular flexibility, cancer nanomedicine has offered opportunities to strengthen antitumor immune responses and to sensitize tumor to immunotherapy. Furthermore, tumor-microenvironment (TME)-responsive nanomedicine has been demonstrated to achieve specific and localized amplification of the immune response in tumor tissue in a safe and effective manner, increasing patient response rates to immunotherapy and reducing the immune-related side effects simultaneously. Here, the recent progress of TME-responsive nanomedicine for cancer immunotherapy is summarized, which responds to the signals in the TME, such as weak acidity, reductive environment, high-level reactive oxygen species, hypoxia, overexpressed enzymes, and high-level adenosine triphosphate. Moreover, the potential to combine nanomedicine-based therapy and immunotherapeutic strategies to overcome each step of the cancer-immunity cycle and to enhance antitumor effects is discussed. Finally, existing challenges and further perspectives in this rising field with the hope for improved development of clinical applications are discussed.

Efficient ancestry and mutation simulation with msprime 1.0

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.